Literature DB >> 35611093

Metagenomic mining of Indian river confluence reveal functional microbial community with lignocelluloytic potential.

Vinay Rajput1, Rachel Samson1,2, Rakeshkumar Yadav1,2, Syed Dastager1,2, Krishna Khairnar3, Mahesh Dharne1,2.   

Abstract

Microbial carbohydrate-active enzymes (CAZyme) can be harnessed for valorization of Lignocellulosic biomass (LCB) to value-added chemicals/products. The two Indian Rivers Ganges and the Yamuna having different origins and flow, face accumulation of carbon-rich substrates due to the discharge of wastewater from adjoining paper and pulp industries, which could potentially contribute to the natural enrichment of LCB utilizing genes, especially at their confluence. We analyzed CAZyme diversity in metagenomic datasets across the sacred confluence of the Rivers Ganges and Yamuna. Functional annotation using CAZyme database identified a total of 77,815 putative genes with functional domains involved in the catalysis of carbohydrate degradation or synthesis of glycosidic bonds. The metagenomic analysis detected ~ 41% CAZymes catalyzing the hydrolysis of lignocellulosic biomass polymers- cellulose, hemicellulose, lignin, and pectin. The Beta diversity analysis suggested higher CAZyme diversity at downstream region of the river confluence, which could be useful niche for culture-based studies. Taxonomic origin for CAZymes revealed the predominance of bacteria (97%), followed by archaea (1.67%), Eukaryota (0.63%), and viruses (0.7%). Metagenome guided CAZyme diversity of the microflora spanning across the confluence of Ganges-Yamuna River, could be harnessed for biomass and bioenergy applications. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-022-03190-7. © King Abdulaziz City for Science and Technology 2022.

Entities:  

Keywords:  CAZymes; Confluence (Sangam); Lignocellulosic; River Ganges; River Yamuna

Year:  2022        PMID: 35611093      PMCID: PMC9124283          DOI: 10.1007/s13205-022-03190-7

Source DB:  PubMed          Journal:  3 Biotech        ISSN: 2190-5738            Impact factor:   2.893


  47 in total

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